Summary

  • 4 minutes

Our goal in this module was to determine if Azure Data Factory would be a good choice for your data-integration needs. You applied the following criteria to guide your decision:

  • Requirement for data integration
  • Coding resources
  • Support for multiple data sources
  • Serverless infrastructure

You applied these criteria to your fictional gaming company. Your analysis helped you determine if Azure Data Factory can help you orchestrate your big data. You evaluated whether Azure Data Factory can help you integrate your data sources and how it can ingest data from on-premises, multicloud, and SaaS data sources.

Many organizations work with big data, which can often be raw, unorganized, and stored in a range of locations. A significant challenge for these organizations is to bring order to this big data and to refine it into actionable business insights. In this module, you learned that Azure Data Factory is a fully managed cloud service that can help you manage complex hybrid extract, transform, load (ETL), ELT, and data-integration projects.

You should now be able to determine whether Azure Data Factory can provide a suitable data-integration solution for your organization. Consider Azure Data Factory when your organization meets one or more of the following criteria:

  • Your data engineers lack the necessary skills to create code to perform data analytics tasks.
  • You have multiple data sources in disparate locations.
  • You want to take advantage of a fully managed, cloud-based solution.

References